Reliability inference for a multicomponent stress-strength model based on Kumaraswamy distribution

doi:10.1016/j.cam.2020.112823

淡江大學機構典藏 > 商管學院 > 統計學系暨研究所 > 期刊論文 > Item 987654321/118258

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/118258

题名:	Reliability inference for a multicomponent stress-strength model based on Kumaraswamy distribution
作者:	Liang Wang;Sanku Dey;Yogesh Mani Tripathi;Shuo-Jye Wu
关键词:	Multicomponent stress–strength model;Kumaraswamy distribution;Maximum likelihood estimation;Generalized pivotal quantity;Asymptotic theory;Bootstrap interval
日期:	2020-10
上传时间:	2020-03-12 12:10:54 (UTC+8)
摘要:	In this paper, inference for a multicomponent stress–strength (MSS) model is studied under censored data. When both latent strength and stress random variables follow Kumaraswamy distributions with common shape parameters, the maximum likelihood estimate of MSS reliability is established and associated approximate confidence interval is constructed using the asymptotic distribution theory and delta method. Moreover, pivotal quantities based generalized point and confidence interval estimates are presented for the MSS reliability. Furthermore, likelihood and generalized pivotal based estimates are also presented when the strength and stress variables have unequal shape parameters. For complementary and comparison, bootstrap confidence intervals are provided as well under common and unequal parameter cases. In addition, to compare the equivalence between strength and stress shape parameters, the likelihood ratio test for hypothesis of interest is also discussed. Finally, simulation study and a real data example are provided to investigate the performance of proposed procedures.
關聯:	Journal of Computational and Applied Mathematics 376, 112823
DOI:	10.1016/j.cam.2020.112823
显示于类别:	[統計學系暨研究所] 期刊論文

文件中的档案:

档案	描述	大小	格式	浏览次数
index.html		0Kb	HTML	190	检视/开启

在機構典藏中所有的数据项都受到原著作权保护.

TAIR相关文章

数据加载中.....